malhajar/Qwen1.5-7B-turkish

Overview

malhajar/Qwen1.5-7B-turkish is a 7.7 billion parameter language model developed by Mohamad Alhajar. It is a fine-tuned version of the Qwen1.5-7B base model, specifically adapted for the Turkish language. The fine-tuning process utilized SFT (Supervised Fine-Tuning) and the Freeze method, focusing on instruction-based learning.

Key Capabilities

• Turkish Language Proficiency: Optimized for understanding and generating text in Turkish.
• Instruction Following: Fine-tuned on the alpaca-gpt4-tr dataset, enabling it to respond effectively to instructions in a chat format.
• Conversational AI: Designed to provide informative answers and engage in dialogue, making it suitable for interactive applications.

Good For

• Turkish Chatbots: Developing AI assistants or chatbots that communicate naturally in Turkish.
• Information Retrieval: Answering questions and providing information in Turkish based on given prompts.
• Turkish NLP Applications: Any application requiring robust Turkish language generation and comprehension capabilities, particularly in an instruction-following context.